Thomas A Gerds

IT University of Copenhagen, København, Capital Region, Denmark

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Publications (118)360.46 Total impact

  • Randi Grøn · Thomas A Gerds · Per K Andersen
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    ABSTRACT: Poisson regression is an important tool in register-based epidemiology where it is used to study the association between exposure variables and event rates. In this paper, we will discuss the situation with 'large n and small p', where n is the sample size and p is the number of available covariates. Specifically, we are concerned with modeling options when there are time-varying covariates that can have time-varying effects. One problem is that tests of the proportional hazards assumption, of no interactions between exposure and other observed variables, or of other modeling assumptions have large power due to the large sample size and will often indicate statistical significance even for numerically small deviations that are unimportant for the subject matter. Another problem is that information on important confounders may be unavailable. In practice, this situation may lead to simple working models that are then likely misspecified. To support and improve conclusions drawn from such models, we discuss methods for sensitivity analysis, for estimation of average exposure effects using aggregated data, and a semi-parametric bootstrap method to obtain robust standard errors. The methods are illustrated using data from the Danish national registries investigating the diabetes incidence for individuals treated with antipsychotics compared with the general unexposed population. Copyright © 2015 John Wiley & Sons, Ltd.
    Statistics in Medicine 10/2015; DOI:10.1002/sim.6755 · 1.83 Impact Factor
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    ABSTRACT: Background Biomarkers predicting response to primary androgen deprivation therapy (ADT) and risk of castration-resistant prostate cancer (CRPC) is lacking. We aimed to analyse the predictive value of ERG expression for development of CRPC.Methods In total, 194 patients with advanced and/or metastatic prostate cancer (PCa) treated with first-line castration-based ADT were included. ERG protein expression was analysed in diagnostic specimens using immunohistochemistry (anti-ERG, EPR3864). Time to CRPC was compared between ERG subgroups using multiple cause-specific Cox regression stratified on ERG-status. Risk reclassification and time-dependent area under the ROC curves were used to assess the discriminative ability of ERG-status. Time to PSA-nadir, proportion achieving PSA-nadir ≤0.2 ng/ml, and risk of PCa-specific death were secondary endpoints.ResultsMedian follow-up was 6.8 years (IQR: 4.9–7.3). In total, 105 patients (54.1%) were ERG-positive and 89 (45.9%) were ERG-negative. No difference in risk of CRPC was observed between ERG subgroups (P = 0.51). Median time to CRPC was 3.9 years (95%CI: 3.2–5.1) and 4.5 years (95%CI: 2.3-not reached) in the ERG-positive and ERG-negative group, respectively. Compared to a model omitting ERG-status, the ERG-stratified model showed comparable AUC values 1 year (77.6% vs. 78.0%, P = 0.82), 2 years (71.7% vs. 71.8%, P = 0.85), 5 years (68.5% vs. 69.9%, P = 0.32), and 8 years (67.9% vs. 71.4%, P = 0.21) from ADT initiation. No differences in secondary endpoints were observed.ConclusionsERG expression was not associated with risk of CRPC suggesting that ERG is not a candidate biomarker for predicting response to primary ADT in patients diagnosed with advanced and/or metastatic PCa. Prostate © 2015 Wiley Periodicals, Inc.
    The Prostate 05/2015; 75(14). DOI:10.1002/pros.23026 · 3.57 Impact Factor
  • European Urology Supplements 04/2015; 14(2):e529. DOI:10.1016/S1569-9056(15)60522-X · 3.37 Impact Factor
  • European Urology Supplements 04/2015; 14(2):e323. DOI:10.1016/S1569-9056(15)60320-7 · 3.37 Impact Factor
  • Michael W Kattan · Thomas A Gerds
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    ABSTRACT: Choosing to replace or maintain an existing cancer staging system is a difficult task. The system plays a critical role in patient counselling and treatment decision making because the staging system conveys prognosis. Many issues may be considered when deciding the preferred system (i.e. old or new), such as the level of evidence for one or more factors included in the system or the general opinions of expert clinicians. However, given the major objective of estimating prognosis on an ordinal scale, we argue that the rival staging system candidates should be compared on their ability to predict outcome. We sought to outline an algorithm that would compare two rival ordinal systems on their predictive ability. We devised an algorithm based largely on the concordance index, which is appropriate for comparing two models in their ability to rank observations. We demonstrate our algorithm with a prostate cancer staging system example. We have provided an algorithm for selecting the preferred staging system based on prognostic accuracy. It appears to be useful for the purpose of selecting between two ordinal prediction models. © The Author(s) 2015.
    Clinical Trials 02/2015; 12(4). DOI:10.1177/1740774515572614 · 1.93 Impact Factor
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    ABSTRACT: Objectives Maternal body mass index (BMI), birth weight, and preschool BMI may help identify children at high risk of overweight as they are (1) similarly linked to adolescent overweight at different stages of the obesity epidemic, (2) linked to adult obesity and metabolic alterations, and (3) easily obtainable in health examinations in young children. The aim was to develop early childhood prediction models of adolescent overweight, adult overweight, and adult obesity.Methods Prediction models at various ages in the Northern Finland Birth Cohort born in 1966 (NFBC1966) were developed. Internal validation was tested using a bootstrap design, and external validation was tested for the model predicting adolescent overweight using the Northern Finland Birth Cohort born in 1986 (NFBC1986).ResultsA prediction model developed in the NFBC1966 to predict adolescent overweight, applied to the NFBC1986, and aimed at labelling 10% as “at risk” on the basis of anthropometric information collected until 5 years of age showed that half of those at risk in fact did become overweight. This group constituted one-third of all who became overweight.Conclusions Our prediction model identified a subgroup of children at very high risk of becoming overweight, which may be valuable in public health settings dealing with obesity prevention.
    Obesity 01/2015; 23(1). DOI:10.1002/oby.20921 · 3.73 Impact Factor
  • Frank Eriksson · Thomas Alexander Gerds · Emmanuel Lesaffre
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    ABSTRACT: The marginal approach and the conditional approach are two different ways to model clustered dental failure time data. We compare the two approaches in the context of a Cox regression analysis, where the aim is to estimate the effect of a covariate (e.g., dental treatment) on the risk of failure. Specifically, we treat within-cluster correlation as if it was introduced by unobserved cluster level covariates, and study the small sample behaviour of the marginal and the conditional approach. We show that in a non-randomized setting where an unobserved cluster variable is correlated with the variable of interest, both the marginal and the conditional approaches can give misleading results. We argue that this is an important message, since most often it is assumed that the frailty term and the covariates of interest are independent.
    Statistical Modelling 12/2014; 14(6):549-566. DOI:10.1177/1471082X14535518 · 0.98 Impact Factor
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    ABSTRACT: Nonsteroidal anti-inflammatory drugs (NSAIDs) are assumed to increase bleeding risk, but their actual relation to serious bleeding in patients with atrial fibrillation (AF) who are receiving antithrombotic medication is unknown.
    Annals of internal medicine 11/2014; 161(10):690-8. DOI:10.7326/M13-1581 · 17.81 Impact Factor
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    ABSTRACT: Background Transit-time flow measurement (TTFM) is a commonly used intraoperative method for evaluation of coronary artery bypass graft (CABG) anastomoses. This study was undertaken to determine whether TTFM can also be used to predict graft patency at one year postsurgery. Methods Three hundred forty-five CABG patients with intraoperative graft flow measurements and one year angiographic follow-up were analyzed. Graft failure was defined as more than 50% stenosis including the string sign. Logistic regression analysis was used to analyze the risk of graft failure after one year based on graft vessel type, anastomatic configuration, and coronary artery size. ResultsNine hundred eighty-two coronary anastomoses were performed of which 12% had signs of graft failure at one year angiographic follow-up. In internal mammary arteries (IMAs), analysis showed a 4% decrease in graft failure odds for every 1mL/min increase in TTFM (OR=0.96, CI=[0.93; 0.99], p=0.005). ROC analysis showed good discriminative ability for TTFM alone AUC=69.5% in IMA grafts. For single-vein grafts the decrease in graft failure odds was 2% for every 1mL/min increase in TTFM (OR=0.98; CI=[0.97; 1.00], p=0.059) and AUC of 59.9%. There were no significant relationships between TTFM and graft failure in other graft types or graft configurations. Conclusion The TTFM method has good discriminative ability for assessing the risk of graft failure in certain graft types within the first year after CABG surgery and is a valuable instrument for intraoperative quality assessment of bypass grafts. doi: 10.1111/jocs.12471 (J Card Surg 2015;30:47-52)
    Journal of Cardiac Surgery 11/2014; 30(1). DOI:10.1111/jocs.12471 · 0.89 Impact Factor
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    ABSTRACT: Background Compelling biomarkers identifying prostate cancer patients with a high risk of progression during active surveillance (AS) are needed. Objective To examine the association between ERG expression at diagnosis and the risk of progression during AS. Design, setting, and participants This study included 265 patients followed on AS with prostate-specific antigen (PSA) measurements, clinical examinations, and 10–12 core rebiopsies from 2002 to 2012 in a prospectively maintained database. ERG immunohistochemical staining was performed on diagnostic paraffin-embedded formalin-fixed sections with a ready-to-use kit (anti-ERG, EPR3864). Men were characterised as ERG positive if a minimum of one tumour focus demonstrated ERG expression. Outcome measurements and statistical analysis Overall AS progression was defined as clinical progression: increased clinical tumour category ≥cT2b by digital rectal examination and ultrasound, and/or histopathologic progression: upgrade of Gleason score, more than three positive cores or bilateral positive cores, and/or PSA progression: PSA doubling time <3 yr. Risk of progression was analysed using multiple cause-specific Cox regression and stratified cumulative incidences (Aalen-Johansen method). Curatively intended treatment, watchful waiting, and death without progression were treated as competing events. Results and limitations A total of 121 of 142 ERG-negative and 96 of 123 ERG-positive patients had complete diagnostic information. In competing risk models, the ERG-positive group showed significantly higher incidences of overall AS progression (p < 0.0001) and of the subgroups PSA progression (p < 0.0001) and histopathologic progression (p < 0.0001). The 2-yr cumulative incidence of overall AS progression was 21.7% (95% confidence interval [CI], 14.3–29.1) in the ERG-negative group compared with 58.6% (95% CI, 48.7–68.5) in the ERG-positive group. ERG positivity was a significant predictor of overall AS progression in multiple Cox regression (hazard ratio: 2.45; 95% CI, 1.62–3.72; p < 0.0001). The main limitation of this study is its observational nature. Conclusions In our study, ERG positivity at diagnosis can be used to estimate the risk of progression during AS. If confirmed, ERG status can be used to individualise AS programmes. Patient summary The tissue biomarker ERG identifies active surveillance patients with an increased risk of disease progression.
    European Urology 11/2014; 66(5). DOI:10.1016/j.eururo.2014.02.058 · 13.94 Impact Factor
  • Jørgen Hilden · Thomas A Gerds
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    ABSTRACT: The 'integrated discrimination improvement' (IDI) and the 'net reclassification index' (NRI) are statistics proposed as measures of the incremental prognostic impact that a new biomarker will have when added to an existing prediction model for a binary outcome. By design, both measures were meant to be intuitively appropriate, and the IDI and NRI formulae do look intuitively plausible. Both have become increasingly popular. We shall argue, however, that their use is not always safe. If IDI and NRI are used to measure gain in prediction performance, then poorly calibrated models may appear advantageous, and in a simulation study, even the model that actually generates the data (and hence is the best possible model) can be improved on without adding measured information. We illustrate these shortcomings in actual cancer data as well as by Monte Carlo simulations. In these examples, we contrast IDI and NRI with the area under ROC and the Brier score. Unlike IDI and NRI, these traditional measures have the characteristic that prognostic performance cannot be accidentally or deliberately inflated. Copyright © 2013 John Wiley & Sons, Ltd.
    Statistics in Medicine 08/2014; 33(19). DOI:10.1002/sim.5804 · 1.83 Impact Factor
  • Thomas A. Gerds · Jørgen Hilden
    Statistics in Medicine 08/2014; 33(19). DOI:10.1002/sim.6212 · 1.83 Impact Factor
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    ABSTRACT: The Net Reclassification Index (NRI) is a very popular measure for evaluating the improvement in prediction performance gained by adding a marker to a set of baseline predictors. However, the statistical properties of this novel measure have not been explored in depth. We demonstrate the alarming result that the NRI statistic calculated on a large test dataset using risk models derived from a training set is likely to be positive even when the new marker has no predictive information. A related theoretical example is provided in which an incorrect risk function that includes an uninformative marker is proven to erroneously yield a positive NRI. Some insight into this phenomenon is provided. Since large values for the NRI statistic may simply be due to use of poorly fitting risk models, we suggest caution in using the NRI as the basis for marker evaluation. Other measures of prediction performance improvement, such as measures derived from the receiver operating characteristic curve, the net benefit function, and the Brier score, cannot be large due to poorly fitting risk functions.
    Statistics in Biosciences 08/2014; DOI:10.1007/s12561-014-9118-0
  • Thomas A Gerds · Per K Andersen · Michael W Kattan
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    ABSTRACT: A predicted risk of 17% can be called reliable if it can be expected that the event will occur to about 17 of 100 patients who all received a predicted risk of 17%. Statistical models can predict the absolute risk of an event such as cardiovascular death in the presence of competing risks such as death due to other causes. For personalized medicine and patient counseling, it is necessary to check that the model is calibrated in the sense that it provides reliable predictions for all subjects. There are three often encountered practical problems when the aim is to display or test if a risk prediction model is well calibrated. The first is lack of independent validation data, the second is right censoring, and the third is that when the risk scale is continuous, the estimation problem is as difficult as density estimation. To deal with these problems, we propose to estimate calibration curves for competing risks models based on jackknife pseudo-values that are combined with a nearest neighborhood smoother and a cross-validation approach to deal with all three problems. Copyright © 2014 John Wiley & Sons, Ltd.
    Statistics in Medicine 08/2014; 33(18). DOI:10.1002/sim.6152 · 1.83 Impact Factor
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    ABSTRACT: We introduce a new approach to competing risks using random forests. Our method is fully non-parametric and can be used for selecting event-specific variables and for estimating the cumulative incidence function. We show that the method is highly effective for both prediction and variable selection in high-dimensional problems and in settings such as HIV/AIDS that involve many competing risks.
    Biostatistics 04/2014; 15(4). DOI:10.1093/biostatistics/kxu010 · 2.65 Impact Factor
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    ABSTRACT: Using a large, contemporary primary care population we aimed to provide absolute long-term risks of cardiovascular death (CVD) based on the QTc interval and to test whether the QTc interval is of value in risk prediction of CVD on an individual level. Digital electrocardiograms from 173 529 primary care patients aged 50-90 years were collected during 2001-11. The Framingham formula was used for heart rate-correction of the QT interval. Data on medication, comorbidity, and outcomes were retrieved from administrative registries. During a median follow-up period of 6.1 years, 6647 persons died from cardiovascular causes. Long-term risks of CVD were estimated for subgroups defined by age, gender, cardiovascular disease, and QTc interval categories. In general, we observed an increased risk of CVD for both very short and long QTc intervals. Prolongation of the QTc interval resulted in the worst prognosis for men whereas in women, a very short QTc interval was equivalent in risk to a borderline prolonged QTc interval. The effect of the QTc interval on the absolute risk of CVD was most pronounced in the elderly and in those with cardiovascular disease whereas the effect was negligible for middle-aged women without cardiovascular disease. The most important improvement in prediction accuracy was noted for women aged 70-90 years. In this subgroup, a total of 9.5% were reclassified (7.2% more accurately vs. 2.3% more inaccurately) within clinically relevant 5-year risk groups when the QTc interval was added to a conventional risk model for CVD. Important differences were observed across subgroups when the absolute long-term risk of CVD was estimated based on QTc interval duration. The accuracy of the personalized CVD prognosis can be improved when the QTc interval is introduced to a conventional risk model for CVD.
    European Heart Journal 03/2014; 35(20). DOI:10.1093/eurheartj/ehu081 · 15.20 Impact Factor
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    ABSTRACT: The concordance probability is a widely used measure to assess discrimination of prognostic models with binary and survival endpoints. We formally define the concordance probability for a prognostic model of the absolute risk of an event of interest in the presence of competing risks and relate it to recently proposed time-dependent area under the receiver operating characteristic curve measures. For right-censored data, we investigate inverse probability of censoring weighted (IPCW) estimates of a truncated concordance index based on a working model for the censoring distribution. We demonstrate consistency and asymptotic normality of the IPCW estimate if the working model is correctly specified and derive an explicit formula for the asymptotic variance under independent censoring. The small sample properties of the estimator are assessed in a simulation study also against misspecification of the working model. We further illustrate the methods by computing the concordance probability for a prognostic model of coronary heart disease (CHD) events in the presence of the competing risk of non-CHD death.
    Biostatistics 02/2014; 15(3). DOI:10.1093/biostatistics/kxt059 · 2.65 Impact Factor
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    ABSTRACT: Treatment options for metastatic colon cancer (mCC) are widening. We prospectively evaluated serial 2-deoxy-2-[18F]fluoro-d-glucose positron-emission tomography/computed tomography (PET/CT) and measurements of tissue inhibitor of metalloproteinases-1 (TIMP-1), carcinoembryonic antigen (CEA), and liberated domain I of urokinase plasminogen activator receptor (uPAR(I)) for early assessment of treatment response in mCC patients.Methods Thirty-three mCC patients scheduled for first-line chemotherapy with capecitabine, oxaliplatin (CAPOX), and bevacizumab participated; 27 were evaluated by PET/CT before treatment, after one and four treatment series. Morphological and metabolic response was independently assessed according to Response Evaluation Criteria in Solid Tumors and European Organization for Research and Treatment of Cancer PET criteria. Plasma TIMP-1, plasma uPAR(I), and serum CEA were determined.ResultsMetabolic response after one treatment course predicted the ability of CAPOX and bevacizumab to induce morphological response after four treatment series with a sensitivity of 80%, specificity of 69%, and odds ratio of 13.9 (95% confidence interval [CI] 1.9; 182). Early metabolically stable or progressive disease was associated with shorter progression-free survival (hazard ratio [HR] = 3.2 [CI 1.3; 7.8]). Biomarker levels at early evaluation were associated with shorter OS (TIMP-1 per unit increase on a log-2-transformed ng/mL scale: HR = 2.6 [CI 1.4; 4.9]; uPAR(I) per 25 fmol/mL increase: HR = 1.5 [CI 1.1; 2.1]).Conclusion This monocentric study demonstrated predictive value of early metabolic PET response and prognostic value of TIMP-1 and uPAR(I) levels in mCC treated with CAPOX and bevacizumab. Results support investigation of PET/CT, TIMP-1, and uPAR(I) guided early treatment adaptation in mCC.
    The Oncologist 01/2014; 19(2). DOI:10.1634/theoncologist.2013-0229 · 4.87 Impact Factor
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    ABSTRACT: Abstract Prediction of postpartum blood transfusion - risk factors and recurrence Anne J Wikkelsø, Sofie Hjortøe, Thomas A Gerds, Ann M Møller, Jens Langhoff-Roos Objective The aim was to find clinically useful risk factors for postpartum transfusion and to assess the joint predictive value in a population of women with a first and second delivery. Methods All Danish women with a first and second delivery from January 2001 to September 2009 who gave birth in a hospital that reported transfusion of red blood cells to a national database: A total of 96.545 women were included. Results Retained placental tissue explained more than all other risk factors in vaginal deliveries. Retained placental tissue at first delivery was associated with postpartum transfusion at a second vaginal delivery, and may also be used as an early predictor in parallel with a history of either placental abruption, postpartum transfusion or caesarean delivery. The positive predictive values of having more than one risk factor was low (2.2% - 2.7%). Conclusions Prediction of postpartum transfusion is difficult. Retained placental tissue is the strongest predictor of postpartum blood transfusion in vaginal deliveries. Retained placental tissue is usually diagnosed for the first time when the bleeding starts, which limits the clinical value of prediction. We need tools for an early diagnosis of retained placenta to intervene early before transfusion is needed.
    The journal of maternal-fetal & neonatal medicine: the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians 12/2013; 27(16). DOI:10.3109/14767058.2013.872095 · 1.37 Impact Factor
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    ABSTRACT: Pregnant women are at an increased risk of venous thromboembolism (VTE). Risk factors for VTE among pregnant women are not sufficiently investigated. To examine pharmacological and non-pharmacological VTE risk factors during pregnancy (antepartum). The population comprised all pregnant women in Denmark aged 15-50 giving birth 2003-2010. Pregnancies were linked on an individual level with national registers for hospital admissions and drug dispenses from pharmacies. Risk of first occurring VTE antepartum was examined with Cox regression models. Out of 299 810 pregnancies, 337 experienced a VTE, incidence rate 1.1 (95% confidence interval [CI] 1.0-1.3) per 1000 pregnancies. Being underweight (body mass index [BMI] < 18.5 kg/m(2) ) was associated with a decreased risk of VTE (hazard ratio [HR] 0.53 [CI 0.29-0.98]) compared to normal weight (18.5 ≤ BMI < 25 kg/m(2) ). Overweight (25 ≤ BMI < 30 kg/m(2) ) increased VTE risk (HR 1.30 [CI 1.01-1.67]) but obesity (BMI ≥ 30 kg/m(2) ) was insignificant (HR 1.14 [CI 0.82-1.58]). A history of VTE was highly significant (HR 72.65 [CI 51.17-103.15]). The youngest (<20 years) and oldest (≥35 years) had insignificantly increased risks (HR 1.45 [CI 0.80-2.62] and HR 1.31 [CI 0.98-1.75], respectively) compared to those aged 20-30 years. Sixteen groups of medications, including anti-infectious medications, hormones, aminosalicylic acid, insulin, and benzodiazepine derivatives, were associated with VTE. The risk of antepartum VTE was increased in women with prior VTE. Compared to normal weight women, being underweight decreased the risk of VTE whereas being overweight increased the risk. Also, the use of several medications was associated with increased risk of VTE. Copyright © 2013 John Wiley & Sons, Ltd.
    Pharmacoepidemiology and Drug Safety 12/2013; 22(12). DOI:10.1002/pds.3536 · 2.94 Impact Factor

Publication Stats

2k Citations
360.46 Total Impact Points


  • 2009–2015
    • IT University of Copenhagen
      København, Capital Region, Denmark
    • Herlev Hospital
      • Department of Pathology
      Herlev, Capital Region, Denmark
  • 2012
    • Catholic University of Louvain
      Лувен-ла-Нев, Walloon, Belgium
  • 2008
    • New York University College of Dentistry
      New York City, New York, United States
  • 2003–2008
    • University of Freiburg
      • Institute of Medical Biometry and Medical Informatics
      Freiburg, Baden-Württemberg, Germany
  • 2005
    • Universitätsklinikum Freiburg
      • Department of Prosthodontics
      Freiburg an der Elbe, Lower Saxony, Germany
  • 2004
    • Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e.V.
      Freiburg, Baden-Württemberg, Germany